How Analytics can Protect Insurers against Fraud?

What is common between Uber, Amazon, EE, Vodafone, Netflix and Progressive? All these companies have recently faced issues due to fraud. In insurance, ghost brokers often target young drivers who wants to cut the cost of their car insurance. Even though it is the ghost brokers who commit the fraud, the customers lose their cash and also risk criminal record. Fraudulent claims from customers is a much bigger concern for insurers.

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How big is Insurance fraud?

The Coalition Against Insurance Fraud, America’s anti-fraud watchdog estimates that nearly $80 billion in fraudulent claims are made in US, annually. Fraud in insurance increases insurance premiums, raises the cost of goods & services and increases spend on investigation and fraud-prevention programs by insurers.

Fraud is one among the many business challenges that insurance industry is facing, as I have outlined in my previous blog. IDC estimates that insurers spend approximately $100 billion on IT, of which $3.3 billion is spent to invest on information security and to counter financial crimes. Four of the five Property & Casualty (P&C) insurers have formal anti-fraud programs. This shows how big fraud is an issue and how insurers are serious about combating fraud.

Analytics to detect insurance fraud

Though application fraud, underwriting fraud and premium fraud are also significant threats for insurance business, claims fraud has been industry’s main focus. Major insurers started deploying new claims platforms to transform their claims management and minimize fraud. There is a spectrum of vendors from big IT players to niche analytics players that is providing claims fraud detection solutions. Zurich’s UK general insurance business recently deployed end-to-end claims management transformation in association with a major insurance vendor which minimises losses associated with fraud.

Manual detection of fraud is next to impossible in insurance industry as it is costly and the sheer volume of claims is too high to handle for any insurance company. Also, the velocity, the variety and the veracity of data generated in the claims handling process made the use of statistical models based on sampling methods, obsolete. Since analytics integrates data from diversified channels and combine internal data into third-party data, effective fraud detection can be made possible. Many insurers have started using analytics techniques such as reporting, descriptive analytics, predictive analytics and prescriptive analytics to detect fraud. For example CNA, the 8th largest commercial P&C insurer implemented analytics and predictive modelling to identify claims fraud. In two years of implementation CNA reportedly saved $6.4 M attributed to recovered or prevented fraudulent claims. Insurers have also started using the latest technologies to detect fraud by combining analytics capabilities to it. In this post, we will see how insurers have started adopting innovative technologies along with analytics to detect insurance fraud, beyond traditional analytics techniques.

Social Network Analysis

A recent AM Best survey found that more than half of companies surveyed, use social media. Life insurance companies appear to be most likely to use social media (65%). Company size is also a driving factor for social media. Larger the company, more likely it is to use social media. Insurers have also started using social media data of policyholders to investigate and detect claims fraud. For example, if a non-smoker applicant light up even occasionally and if his/her social pages has the traces of that information it can be detected via Social Network Analysis (SNA) tools. SNA tools scans large amounts of data from business rules, statistical methods, pattern analysis and network linkage analyses to uncover possibilities for fraud.

Drones

Insuring drones and wearables is going to be difficult for insurers as there are multitude of insurance liability and coverage issues. However, insurers have started using drones for their benefit by adopting it in claims adjusting. USAA appointed its first drone pilot for claims handling. With drones in place for claims handling, insurers would no longer need to climb dangerous chimney or to visit catastrophe sites. Also, the data analysis from drones are used to detect insurance fraud. A British Company, ‘Air & Space Evidence’ detected a fraud case after Hurricane Katrina with the help of drones. The couple who claimed that their home in New Orleans was severely damaged by wind and water was found fraudulent when aerial photos showed that the house was intact after Hurricane Katrina.

Wearables

One third of the insurer’s surveyed are already using wearables for customer engagement according to Accenture’s 2015 technology vision report. We all know that disruptive technologies such as telematics and wearables (Oscar’s Misfit, Fitbit and the Apple Watch) has also been started using for calculating customized premiums. What’s new is, in Canada, data from a Fitbit wristband is used by a personal injury lawyer to support his client’s case. Soon, these technologies will also be used to detect insurance fraud as the data collected from these devices will become fodder for criminal and civil litigation. Insurers now have many reasons to turn to innovative technologies and analytics to protect themselves against fraud.

Please share your thoughts on how you have seen innovative technologies and analytics is helping insurers to combat fraud and transforming the insurance industry. In the next few blogs, I will try and explore analytics’ role in the insurance industry in further detail.

This blog is written by Karthick Paulraj, Analytics Consultant at BRIDGEi2i

About BRIDGEi2i:BRIDGEi2iprovides Business Analytics Solutions to enterprises globally, enabling them to achieve accelerated business impact harnessing the power of data. BRIDGEi2i’s Insurance Industry solutions bring in a unique combination of advanced analytics techniques and domain experience to help businesses develop a clear understanding of the market landscape, prioritize marketing channels and transform digital data into actionable insights to deliver incremental marketing return on investment. To know more visit www.bridgei2i.com

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The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position or viewpoint of BRIDGEi2i.

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